ArticleClinical ophthalmology (Auckland, N.Z.)2025
Comparing Ophthalmologist and Artificial Intelligence Chatbot Responses to Patient Questions.
Article in Clinical ophthalmology (Auckland, N.Z.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Accuracy and Effectiveness of AI-Powered Systems in Patient Counseling, Education, and Management in Optometry and Related Eye-Care Settings: A Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: We evaluated the ability of ChatGPT, an Artificial Intelligence (AI) Chatbot, to respond to patient eye health queries. Methods: A retrospective, cross-sectional analysis of eye health questions and physician responses posted on the American Academy of Ophthalmology (AAO) "Ask an Ophthalmologist" forum was performed on a random sample from January 2016 to December 2022. We compared board-certified ophthalmologists' responses to ChatGPT (version GPT-4o, OpenAI) responses in September 2024. Primary outcomes included ophthalmologist-rated accuracy of ChatGPT and AAO responses using a 7-point Likert scale, as well as ophthalmologists' preferences between the two responses. Secondary outcomes assessed differences in readability, empathy, and response length between ChatGPT and ophthalmologists. Results: A random sample 250 questions and responses from 41 board-certified ophthalmologists were evaluated. ChatGPT and AAO responses had similar mean accuracy ratings (5.8 [SD=1.1] vs 5.5 [SD=1.1], p=0.07). Evaluators preferred ChatGPT over physician responses in half (49.5%) the cases. Ophthalmologist responses were easier to understand, with a lower mean Flesch-Kincaid Grade Level (Grade 11.0 [SD=2.7] vs Grade 12.7 [SD=1.9], p<0.001). Ophthalmologist responses were also significantly shorter than ChatGPT responses (80.6 [SD=56.4] words vs (337.8 [SD=141.6] words, p<0.001). Empathy ratings did not differ significantly between ChatGPT and ophthalmologists (4.4 [SD=0.6] vs 4.4 [SD=0.6], p=0.5). Conclusion: Our findings suggest that Chatbot responses were as frequently preferred as physician responses, rated with higher accuracy, and demonstrated comparable empathy in addressing online patient eye health queries. AI chatbots may assist in drafting initial responses to patient concerns, potentially improving efficiency and reducing physician workload.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.